• Journal of the Korean Geographical Society
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• v.43 no.1
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• pp.104-116
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• 2008

Overheated speculation areas which have high potential of becoming speculative are the target of many real estate policies. This paper proposes a model for spatial patterns of house price volatility and suggests a spatial pattern of overheated speculation areas. House prices are determined by economic behaviors of sellers and buyers who have rational or adaptive expectations. Spatial patterns of house price volatility are formed by tendencies of their economic behavior. If there is a majority of adaptive sellers and buyers in an area, it may appear as a "hotspot" by showing high volatility of house prices and simultaneous price increases. Overheated speculation areas are formed by adaptive sellers and buyers who want to realize maximum expectation profit, therefore these areas patterns are defined as hotspot patterns of price volatility.

• Proceedings of the CALSEC Conference
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• 2005.11a
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• pp.147-153
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• 2005

When a customer wants to buy an item at the Internet shopping mall, one of the difficulties is to decide when to buy the item because its price changes over time. If the shopping mall can be able to recommend appropriate buying points, it will be greatly helpful for the customer. Therefore, in this presentation, we propose a method to recommend buying points based on the time series analysis using a database that contains past prices data of items. The procedure to provide buying points for an item is as follows. First, we search past time series patterns from the database using normalized similarity, which are similar to the current time series pattern of the item. Second, we analyze the retrieved past patterns and predict the future price pattern of the item. Third, using the future price pattern, we recommend when to buy the item.

• Proceedings of the Korea Multimedia Society Conference
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• 2004.05a
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• pp.491-494
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• 2004

최근 인터넷 쇼핑몰에서 상품을 구매하는 고객들에게 편의성과 효율성을 제공하기 위하여 구매자들의 선호도나 가격에 맞는 상품을 추천해 주는 연구들이 활발하게 진행되고 있다. 그러나 이러한 상품을 추천하는 연구들은 다양하게 발전하고 있지만 추천된 상품들의 구매시점에 관한 연구는 찾아보기 어렵다. 이에 본 논문에서는 인터넷 쇼핑몰의 적극적인 마케팅 일환으로 상품을 구매할 시점을 추천해 주는 방안을 제안한다. 이를 위하여 과거의 판매 기록 데이터베이스에 있는 판매가격의 기준 시계열 패턴과 유사한 시계열 패턴을 정규화 변환된 유사도로써 검색한다. 검색된 과거 가격 패턴을 기준으로 미래 가격 패턴을 분석하여, 미래 가격 패턴의 변화에 따라 상품 구매시점을 추천한다. 또한 본 논문에서는 이러한 구매시점을 추천하는 상품 추천 시스템을 설계한다.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.11-20
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• 2007

Even though much research has been performed to recommend favorite items to the buyers in the internet shopping mall, to the best of our knowledge. it is hard to find previous research on the recommendation of buy points. In this paper, we propose a method which can be used to recommend buy points of an item to the buyers. To do this, a database containing normalized price patterns is constructed from the archive of past prices. Then, the future price pattern is retrieved from the database based on the similarity. Here, regression analysis is used to find and analyze the elements that affect the price. We also present performance results showing that the proposed method can be useful for shopping malls.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.508-510
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• 2003

주식 가격의 결정은 시장 내 수요와 공급에 의해서 결정되며, 가격 변동은 일정한 패턴으로 움직인다고 가정한다. 이러한 패턴을 찾아내어 주식가격의 변동을 예측하는 분석 방법을 기술적 분석이라 한다. 기술적 분석에서는 수요.공급의 변화에 의해 추세가 변동되고, 모든 형태의 주가모형은 반복하려는 경향을 보인다고 가정한다. 이러한 가정하에 본 논문에서는 한국주가지수 200의 과거지수와 거래량을 분석하고, 일정한 패턴을 이용하여 미래의 지수를 예측하는 방법을 연구하였다.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.819-829
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• 2017

The aim of this study is to analyze intraday price momentum. When price trends are formed, price momentum is the phenomenon that future prices tend to follow the trend. When the market opened and closed, a U-shaped trading volume pattern in which the trading volume was concentrated was observed. In this paper, we defined price momentum as the 10 minute trend after market opening is maintained until the end of market. The strategy is to determine buying and selling in accordance with the price change in the initial 10 minutes and liquidating at closing price. In this study, the strategy was empirically analyzed by using minute data, and it showed effectiveness, indicating the presence of an intraday price momentum. A pattern in which returns are increasing at an early stage is called a J-shaped pattern. If the J-shaped pattern occurs, we have found that the price momentum phenomenon tends to be stronger than otherwise. The DTW algorithm, which is well known in the field of pattern recognition, was used for J-shaped pattern recognition and the algorithm was effective in predicting intraday price movements. This study showed that intraday price momentum exists in the KOSPI200 futures market.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.1
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• pp.183-201
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• 2022

Estimating the implicit value of housing assets is a very important task for participants in the housing market. Until now, such estimations were usually carried out using multiple regression analysis based on the inherent characteristics of the estate. However, in this paper, we examine the estimation capabilities of the Artificial Neural Network(ANN) and its 'Deep Learning' faculty. To make use of the strength of the neural network model, which allows the recognition of patterns in data by modeling non-linear and complex relationships between variables, this study utilizes geographic coordinates (i.e. longitudinal/latitudinal points) as the locational factor of housing prices. Specifically, we built a dataset including structural and spatiotemporal factors based on the hedonic price model and compared the estimation performance of the models with and without geographic coordinate variables. The results show that high estimation performance can be achieved in ANN by explaining the spatial effect on housing prices through the geographic location.

• The Journal of Society for e-Business Studies
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• v.16 no.2
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• pp.19-37
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• 2011

With the advancement of Internet, electronic commerce has rapidly expanded and considered as a major retail channel. In the early days of the Internet, many studies compared offline and online stores on their price level and dispersion. Since e-commerce is considered matured, we need to see price change behavior in e-commerce rather than comparing it with traditional channels. Thus, this study investigated the trend of price changes in e-commerce. The data that was gathered from a price comparison site also contained six product categories. The decrease in minimum and average price was identified and the increase in maximum price was also identified. The critical factors in the increase of maximum price are number of sellers (positive effect) and the time span after a product was released (negative effect). The differences in price changes between product categories were also investigated.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2012.05a
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• pp.162-163
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• 2012

유기태양전지의 효율을 향상시키기 위하여 광학적 기능을 갖는 패턴을 유기태양전지 상부에 다이렉트 프린팅 기술을 이용하여 형성하였다. 다이렉트 프린팅 기술은 포토리소그래피, 이빔리소그래피, 등 패턴을 형성하는 다른 기술에 비해 공정이 간단하며 가격이 저렴하다. 유기태양전지에 형성된 광학적 기능을 갖는 패턴은 투과도를 증가시키는 패턴과 광산란을 증가시키는 패턴이다. 광학적 기능을 갖는 패턴을 유기태양전지에 형성하여 최대 6.8 %의 효율이 증가하였다.

• Journal of Energy Engineering
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• v.10 no.1
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• pp.17-23
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• 2001

전력산업 구조개편에 따른 발전부문의 경제급전 추구로 인하여 구 동안 가스산업에서 수급조절역할을 담당하던 발전용 수요의 감소로 수급불균형 심화가 예상되고 결국에는 저장설비의 구축에 막대한 자본이 소요될 것으로 보인다. 이에 본 연구에서는 분석모형을 통하여 이러한 영향들을 계량적으로 분석하고 그 원인을 밝힘으로써 전력산업 구조개편에 대응한 향후의 천연가스 수급정책 방향을 제시하였다. 연구결과에 의하면, 경제급전의 추구로 인해 발전용 수요가 기존 예측치 대비 약 40∼50% 수준으로 급감하여 소요저장탱크기수는 1∼2기 정도 감소하지만, 발전용 수요의 수급조절능력의 약화로 천연가스 수요패턴은 더욱 악화되는 것으로 분석되었다. 또한 필요수입 보전주의에 따른 가격결정방식의 소비자가격이 상승되는 것으로 보아 저장설비에 과다투자가 이루어지는 것으로 판단할 수 있다. 결국, 도시가스의 수요패턴이 현상태를 유지하는 경우, 발전부문의 경제급전시 가스산업에서는 수요패턴의 약화로 저장시설에의 과다설비투자가 불가피하며 이는 소비자가격의 상승으로 이어질 것으로 예상된다. 따라서 향후 가스산업에서는 다양한 수요관리 방안과 도입량 조절 등을 통한 수요패턴 개선노력이 시급할 것으로 판단된다.